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2023-06-02review of previous bug fixJSDurand
Generally speaking the algorithm now works correctly and produces the right shape of forest for the test ambiguous grammar as well. It does not correctly perform the "reductions". It seems that I deliberately disabled this part of the functionalities in a previous debugging tour. So I have to enable it again and see if it works.
2023-06-02abnf: a skeleton for an ABNF parserJSDurand
2023-06-02Fix a bug of duplication from planting after sploingJSDurand
I should have staged and committed these changes separately, but I am too lazy to deal with that. The main changes in this commit are that I added the derive macro that automates the delegation of the Graph trait. This saves a lot of boiler-plate codes. The second main change, perhaps the most important one, is that I found and tried to fix a bug that caused duplication of nodes. The bug arises from splitting or cloning a node multiple times, and immediately planting the same fragment under the new "sploned" node. That is, when we try to splone the node again, we found that we need to splone, because the node that was created by the same sploning process now has a different label because of the planting of the fragment. Then after the sploning, we plant the fragment again. This makes the newly sploned node have the same label (except for the clone index) and the same children as the node that was sploned and planted in the previous rounds. The fix is to check for the existence of a node that has the same set of children as the about-to-be-sploned node, except for the last one, which contains the about-to-be-planted fragment as a prefix. If that is the case, treat it as an already existing node, so that we do not have to splone the node again. This is consistent with the principle to not create what we do not need.
2023-02-28Add a type Reducer for recording extra reductionsJSDurand
In the chain-rule machine, we need to skip through edges whose labels are "accepting", otherwise the time complexity will be high even for simple grammars. This implies that we will skip some "jumping up" in the item derivation forest. So we need to record these extra jumping up, in order to jump up at a later point. This Reducer type plays this role. But I still need more experiments to see if this approach works out as I intended.
2023-02-27before a major refactorJSDurand
I decide to adopt a new approach of recording and updating item derivation forests. Since this affects a lot of things, I decide to commit before the refactor, so that I can create a branch for that refactor.
2023-02-12Added the functionality of split or clone.JSDurand
I need more than the ability to clone nodes: I also need to split the nodes. Now this seems to be correctly added.
2023-02-03Finally produced the first correct forestJSDurand
Finally the prototype parser has produced the first correct forest. It is my first time to generate a correct forest, in fact, ever since the beginning of this project.
2023-01-28a prototype of an item derivation forestJSDurand
It seems to be complete now, but still awaits more tests to see where the errors are, which should be plenty, haha.
2023-01-22forest: clone correctlyJSDurand
Now the forest can detect if a node is packed or cloned, and correctly clones a node in those circumstances. But it still needs to be tested.
2023-01-20chain: a prototype is added.JSDurand
I have an ostensibly working prototype now. Further tests are needed to make sure that the algorithm meets the time complexity requirement, though.
2023-01-13forest seems to be completedJSDurand
I seem to have finished the implementation of forests. Now it remains the implementation of the chain-rule machine, of which I have a rough plan now.
2023-01-11Record left-linear expansion and forest formatJSDurand
Now the grammar will record the left-linear expansions when generating the nondeterministic finite automaton frmo its rules, and will record whether an edge in the nondeterministic finite automaton comes from a left-linear expansion. The latter is needed because while performing a chain-rule derivation, we do not need the left-linear expanded derivations in the "first layer". This might well have been the root cause of the bad performance of the previous version of this package. Also I have figured out how to properly generate and handle parse forests while manipulating the "chain-rule machine".
2023-01-05singly labelled graphsJSDurand
Now I have a new type of labelled graphs, which can index vertices by labels, but not index edges by labels. The biggest difference is that I do not have to keep a hashmap of edge targets by labels, and I do not have to guard against the duplication of nodes with the same set of edges. I guard against nodes with the same label, though. Also, in this graph, both vertices and edges have one label at a time, whereas in the previous labelled graph there can be a multitude of edges between the same source and target nodes, but with different labels. Now it remains to test this type of graphs, and to think through how we attach forest fragments to nondeterministic finite automata edges, and how to join forest fragments together while skipping nullable edges, in order to finish the "compilation" part.
2023-01-03structural change: separate crates outJSDurand
I put functionalities that are not strictly core to separate crates, so that the whole package becomes more modular, and makes it easier to try other parsing algorithms in the future. Also I have to figure the forests out before finishing the core chain-rule algorithm, as the part about forests affects the labels of the grammars directly. From my experiences in writing the previous version, it is asking for trouble to change the labels type dramatically at a later point: too many places need to be changed. Thus I decide to figure the rough part of forests out. Actually I only have to figure out how to attach forests fragments to edges of the underlying atomic languages, and the more complex parts of putting forests together can be left to the recorders, which is my vision of assembling semi-ring values during the chain-rule machine. It should be relatively easy to produce forests fragments from grammars since we are just trying to extract some information from the grammar, not to manipulate those information in some complicated way. We have to do some manipulations in the process, though, in order to make sure that the nulling and epsilon-removal processes do not invalidate these fragments.